TEM EDS Standardless Quantification

[Sheri Singerling]

Hi all,

I'm a very new DTSA-II user. I'm attempting to quantify STEM EDS spectra collected from FIB-sections of SiC. I've already done this using the Bruker software that came with our detector, but I'd like a bit more control over the quantification to try and resolve some weirdness (non 1:1 ratios of Si to C) I'm seeing in a few samples. In any case, I'm having trouble figuring out how to do a Cliff Lorimer quantification for thin films without any standard spectra. We use theoretical k-factors with the Bruker software, and I've been told our detector and microscope have yielded very reliable data, even for low Z elements like C, in the past using this methodology with our equipment (Nion UltraSTEM with a windowless SDD detector).

My question for the forum is, is DTSA-II able to do standardless quantification of thin films? If so, how do I go about doing that? The great tutorial videos that Nicholas has on YouTube seem more geared towards spectra from thick samples and using standards, unless I've missed something. Thanks in advance!

[Nicholas Ritchie]

You are correct that DTSA-II is more geared towards bulk microanalysis.  A few years ago I did add the ability to quantify STEM spectra using Watanabe's zeta factors.  However, this mechanism is also a standards-based method.  It is a little less cumbersome than Cliff-Lorimer because you can use films of pure elements or simple compounds as your standards.  However, it remains a standards based method.  I understand that Oxford has developed a rather clever standardless zeta-factor algorithm but I've never used it.  IT may be the closest to what you sound like you want.

If you are interested in developing TEM EDS algorithms, I'd be happy to discuss ways we could potentially work on this together.

Nicholas

[Sheri Singerling]

Gotcha, thanks for the clarification! I'm always willing to learn more about X-ray microanalysis, but my programming skills are pretty bare-bones at the moment, so I'm not sure I'd be of much use in developing algorithms. That being said, I'm hoping to learn Python in the coming weeks with the extra downtime I have not being able to do lab work at the moment. If the algorithms you have in mind aren't too advanced for a novice, it might be a great way to immerse myself in Python!